Paper Title:
A Smooth Clustering Algorithm Based on Parameter Free Filled Function
  Abstract

In this paper, we propose an algorithm to find centers of clusters based on adjustable entropy technique. A completely differentiable non-convex optimization model for the clustering center problem is constructed. A parameter free filled function method is adopted to search for a global optimal solution of the optimization model. The proposed algorithm can avoid the numerical overflow phenomenon. Numerical results illustrate that the proposed algorithm can effectively hunt centers of clusters and especially improve the accuracy of the clustering even with a relatively small entropy factor.

  Info
Periodical
Advanced Materials Research (Volumes 143-144)
Edited by
H. Wang, B.J. Zhang, X.Z. Liu, D.Z. Luo, S.B. Zhong
Pages
389-393
DOI
10.4028/www.scientific.net/AMR.143-144.389
Citation
Q. Wu, L. X. Yuan, "A Smooth Clustering Algorithm Based on Parameter Free Filled Function", Advanced Materials Research, Vols. 143-144, pp. 389-393, 2011
Online since
October 2010
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